Manufacturing Digital: Getting a big impact from Big Data: Part Two
September 25, 2013-
By Sebastian Mamro
Apply big data insights during contract negotiations
Sales people can now use these insights as they negotiate prices with each individual customer. Using software and mobile devices, a manufacturer’s sales team can construct the highest value deal for both the customer and for the vendor. This approach uses tools that give sales the ability to combine or unbundle products, make substitutions, change payment terms, adjust currency exchange rates, and upsell and cross-sell more products – based on the individual customer’s situation.
This gives sales people the power to demonstrate why a certain price is justified, based on the specific value it delivers to the individual customer. For companies working at the commodity product level, it can move the discussion beyond a focus based solely on price, and instead capture those opportunities for value-added services that command a higher price.
Sales management can monitor sales team activity using analytics that incorporate best practices. With big data analytics, they’re able to evaluate how individual salespeople are performing. For example, chemical manufacturer sales managers can compare the level of discounting between salespeople and across regions. They can see results updated daily on a computer dashboard to gain a much better assessment of an individual’s contributions to profit performance and identify action areas for improvement.
Yield optimisation: The next stage in using big data for manufacturing
Some leading chemical manufacturers are taking the sales performance advantages offered by the latest technology solutions to a new level called “yield optimisation.” This borrows an idea from the airline industry, where companies must constantly balance supply with demand and price accordingly. Chemical manufacturers are now incorporating data that helps optimise any deal to match production capacity and timing of product delivery.
Chemical manufacturers must constantly adjust production operations, depending on raw material availability, plant capacity, environmental impacts and, of course, contract orders. It therefore makes sense to integrate production processes and timing so that the entire supply chain is incorporated in pricing practices. Using big data, contract negotiations can now take place in real time. With the latest product schedules at the fingertips of the sales team, all this information becomes part of the process, and it allows pricing to be adjusted “on the fly” to match production priorities or constraints against customer needs and requests.
Outperform competitors by using the full power of big data
By adopting new sales effectiveness technologies, chemical manufacturers can exploit the potential of big data they already collect through existing systems to help maximise the value and profitability of every contract. Critical information can be automatically communicated where it is needed, so that sales people can be much more knowledgeable – therefore much more effective – in achieving better prices and margins during contract negotiations.
In a world of increasing competition, volatile raw material costs and price discounting pressures, big data offers an unprecedented opportunity to dramatically improve sales performance and profitability for chemical manufacturers. Those who seize the opportunity will be able to outperform their competitors by using the full potential of big data throughout their organisation.
Big savings from big data for global petrochemical company
One of the largest petrochemical companies in the world was able to optimise its approach to sales and pricing for its business-to-business fuels and lubricants segment by using big data applications. The company faced significant challenges trying to manage pricing worldwide since each region of the company – and each business unit within the region – set prices differently. To help eliminate the resulting negative margin transactions that no one could be held accountable for, the company developed more efficient and integrated end-to-end pricing processes based on its use of big data.
The implementation of big data applications helped the company’s sales and pricing managers to optimise prices based on market conditions. This was integrated with the company’s existing SAP system to deliver pricing performance accountability across the organisation as well.
Following the implementation, this chemical manufacturer was able to virtually eliminate negative margin transactions, leading to an improvement in annual margin of $350 million. The company is also able to deliver automated and enforceable pricing processes and workflow across all its business units and regional offices.